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from typing import Dict, Any
import spacy
from sklearn.datasets import make_classification
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from huggingface_hub import hf_hub_download
from joblib import load
SPACY_MODEL = spacy.load('en_core_web_trf', disable=['parser']) # Largest, slowest, most accurate model
from environs import Env
class EndpointHandler:
def __init__(self, path: str):
env = Env()
env.read_env()
model_path = env.str("MODEL_PATH")
downloaded_model_path = hf_hub_download(
repo_id="PDAP/url-relevance-models",
subfolder=model_path,
filename="model.joblib"
)
self.model = load(downloaded_model_path)
def __call__(self, inputs: Dict[str, Any]) -> Dict[str, str]:
# Expecting input like: {"inputs": "<html>...</html>"}
html = inputs["inputs"]
return {"label": str(self.model)}
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